Find the solution set of 2x 3y = 5. Answer: We solve for x = (5 + 3y)/2. Hence the solution space consists of all vectors of the form

Size: px
Start display at page:

Download "Find the solution set of 2x 3y = 5. Answer: We solve for x = (5 + 3y)/2. Hence the solution space consists of all vectors of the form"

Transcription

1 Math 2 Homework #7 March 4, Find the solution set of 2x 3y = 5. Answer: We solve for x = (5 + 3y/2. Hence the solution space consists of all vectors of the form ( ( ( ( x (5 + 3y/2 5/2 3/2 x = = = + y, y y where y is an arbitrary real number Find the solution set of 2x 3y = x 4y = 2 Answer: In matrix form the system is ( ( ( 2 3 x =. 4 y 2 The augmented matrix is ( We reduce to row echelon form by first interchanging the rows and then subtracting 2 times the first row from the second: ( ( M The simplified system of equations is x 4y = 2 5y = 4. Backsolving we get y = 4/5 and then x = 2 + 4y = 2 6/5 = 6/5. Hence the solution is ( 6/5, 4/5 T Find the solution set of 2x 3y = 5 x + 4y = 7 Answer: In matrix form the system is ( ( ( 2 3 x 5 =. 4 y 7 The augmented matrix is (

2 We reduce to row echelon form by first interchanging the rows and then subtracting 2 times the first row from the second: ( ( M The simplified system of equations is x + 4y = 7 y = 9. Backsolving we get y = 9/ and then x = 7 4y = 7 36/ = 4/. Hence the solution is (4/, 9/ T Find the solution set of Answer: In matrix form the system is The augmented matrix is 4x + 7y + 5z = 8 2x + y z = ( ( x y = z ( 8. ( We reduce to row echelon form by first interchanging the rows and then subtracting 2 times the first row from the second: ( ( 2 2 M The simplified system is 2x + y z = 9y + 3z = 8 To backsolve we first set the free variable z = t. Next we solve for y = 2 t/3. Finally we solve for x = (y z/2 = 2t/3. Hence the solutions are the vectors of the form x = ( x y z = ( ( 2t/3 2 t/3 = 2 + t t ( 2/3 / Find the solution set of the system Ay = b, where ( A = and b = ( 5 6 3

3 Answer: In MATLAB we do the following A = [4 2-5; ; ]; b = [-5 6 3] ; M=[A b] M(2,: = M(2,: - M(2,*M(,:/M(,; M(3,: = M(3,: - M(3,*M(,:/M(,; M(3,: = M(3,: - M(3,2*M(2,:/M(2, /2-3/2 The simplified system is 4y + 2y 2 5y 3 = 5 y 2 + y 3 /2 = 3/2 To backsolve, we first set the free variable y 3 = t. Next we solve for y 2 = 3/2 + y 3 /2 = (3 + t/2. Finally, we solve for y = ( 5 2y 2 + 5y 3 /4 = [ 5 (3 + t+ 5t]/4 = 2 + t. Hence our solutions are all vectors of the form y = ( y y 2 y 3 = ( 2 + t (3 + t/2 t = ( 2 3/2 + t ( / Find the solution set of the system Ay = b, where ( ( A = and b = Answer: In MATLAB we do the following A=[-3-3 ;8 7-2;8 6 -]; b=[4-8 -5] ;

4 [A b] M(2,: = M(2,: - M(2,*M(,:/M(,; M(3,: = M(3,: - M(3,*M(,:/M(,; M(3,: = M(3,: - M(3,2*M(2,:/M(2, /3 8/3 /3 /3 The simplified system is 3y 3y 2 + y 3 = 4 y 2 + 2y 3 /3 = 8/3 y 3 /3 = /3 Backsolving we get y 3 =. Next y 2 = 8/3 + 2/3 = 2. Finally, y = ( 4 3y 2 + y 3 /3 =. Hence the only solution is y = (, 2, T Find the solution set of the system Ay = b, where ( A = and b = Answer: Using MATLAB we do the following ( A=[ ; ; 5 2 8]; b=[ ] ; [A b] M(2,: = M(2,: - M(2,*M(,:/M(,; M(3,: = M(3,: - M(3,*M(,:/M(,;

5 M(3,: = M(3,: - M(3,2*M(2,:/M(2, /7-4/7 88/7-6/7 369/28 2/7 The simplified system of equations is 7y + 7y 2 8y 3 3y 4 = 37 4y 2 6y 3 /7 4y 4 /7 = 88/7 6y 3 / y 4 /28 = 2/7 To backsolve, we first set the free variable y 4 = t. Then we solve for y 3 = ( t/4/6 = t/8. Next, Finally y 2 = (88/7 + 6y 3 /7 + 4y 4 /7/4 = [88 + 6( t/8 + 4t]/28 = [ t]/28 = 2 + 4t/4. y = [ y 2 8y 3 3y 4 ]/7 = [ (2 + 4t/4 8( t/8 3t]/7 = 3t/4. Hence the solutions are the vectors y = 3t/ t/ t/8 t = t 3/4 4/4. 23/ Find the solution set of the system Ay = b, where A = ( and b = ( 5 3 9

6 Answer: Using MATLAB we do the following A=[ ; ; ]; b=[5-3 9] ; M=[A b] M(2,: = M(2,: - M(2,*M(,:/M(,; M(3,: = M(3,: - M(3,*M(,:/M(,; M(3,: = M(3,: - M(3,2*M(2,:/M(2, /4 25/8 8-9/8-5/8-83/4-262/7-67/4 63/2 M(2,: = 8*M(2,:; M(3,: = 4*M(3,: The simplified system of equation is 8y 6y 2 + 9y 3 + 8y 4 y 5 = 5 4y y y 4 9y 5 = 5 83y 3 524y 4 67y 5 = 44 To backsolve, we first set the free variables y 4 = s and y 5 = t. The we solve for y 3 = [ s 67t]/83. Next, y 2 = [5 + 25y y 4 9y 5 ]/4 = [5 + 25( s 67t/83 = 44s 9t]/4 = [ 65 82s 73t]/83.

7 and finally, y = [5 + 6y 2 9y 3 8y 4 + y 5 ]/8 = [5 + 6( s + 73t/83 9( s 67t/83 8s + t]/8 = [ s 44t]/83. Hence the solutions are the vectors [ s 44t]/83 [ 65 82s 73t]/83 y = [ s 67t]/83 s t 528/83 445/83 44/83 65/83 82/83 73/83 = 44/83 + s 524/83 + t 67/ Find the solution set of the system Ay = b, where A = ( ( 3 and b = 6 Answer: Using MATLAB we do the following: A=[ ; ; ]; b = [3 6] ; [A b] M(2,: = M(2,: - M(2,*M(,:/M(,; M(3,: = M(3,: - M(3,2*M(2,:/M(2, /2-2 -5/2-5/2 -/2-3/ /5

8 M(2,: = -2*M(2,:; M(3,: = -5*M(3,: The simplified system of equations is 2y + 3y 2 + 6y 3 7y 4 y 5 = 3 5y 2 + 4y 3 + 5y 4 + 5y 5 = 3y 3 y 4 9y 5 = 83 To backsolve, we first set the free variables y 4 = s and y 5 = t. Then we solve for y 3 = [ 83 + s + 9t]/3. Next, y 2 = [ 4y 3 5y 4 5y 5 ]/5 = [ 4( 83 + s + 9t/3 5s 5t]/5 = [23 7s 37t]/3. and finally, y = [3 3y 2 6y 3 + 7y 4 + y 5 ]/2 = [3 3(23 7s 37t/3 6( 83 + s + 9t/3 + 7s + t]/2 = 8 2s + 6t. Hence the solutions are the vectors 8 2s + 6t [23 7s 37t]/3 y = [ 83 + s + 9t]/3 s t /3 7/3 37/3 = 83/3 + s +/3 + t 9/ The matrix ( 2 3 is the reduced row echelon form of the augmented matrix [A, b] representing the system Ax = b. Is the system inconsistent? Answer: Consistent.

9 The matrix ( 2 is the reduced row echelon form of the augmented matrix [A, b] representing the system Ax = b. Is the system inconsistent? Answer: Inconsistent Find all solutions of the homogeneous system Ax = where ( 2 A =. Are there solutions other than the zero vector? Is the coefficient matrix singular? Answer: Using row operations we reduce A to row echelon form. ( 2 A. We now see that the only solution of the homogeneous system is the zero vector (, T. Hence the matrix is nonsingular Find all solutions of the homogeneous system Ax = where ( A =. Are there solutions other than the zero vector? Is the coefficient matrix singular? Answer: Using row operations we reduce A to row echelon form ( ( A. We now see that the only solution of the homogeneous system is the zero vector (, T. Hence the matrix is nonsingular Is the matrix A = ( 4 2 singular? If it is nonsingular find A. Answer: We augment A with the identity and perform row operations: ( ( ( 4 2 /2 2 /4 /4 Hence A is nonsingular and A = ( /2. /4

10 Is the matrix A = ( 2 2 singular? If it is nonsingular find A. Answer: We augment A with the identity and perform row operations: ( [A, I] /2 /2. Hence A is nonsingular and ( A = /2 / Does the system a x + a 2 x 2 + a 3 x 3 = b a 2 x + a 22 x 2 + a 23 x 3 = b 2 have a unique solution? Answer: No. There are fewer equations than unknowns, so there are free variables. There is either no solution or there are many solutions For which values of a and b do the following equations have a solution? ( ( ( 2 4 u 3 5 v = a w b Answer: The augmented matrix is ( a b We use row operations to reduce this to row echelon form ( 2 4 b/2 2 (2a 3b/2. (3b 2a/2 This system will be consistent if and only if 3b 2a = List as many properties as you can of an invertible matrix. Answer: Suppose that A is invertible. Then: ( A is nonsingular. (2 The only solution of the homogeneous system Ay = is the zero vector. (3 The equation Ax = b has a unique solution for any right hand side b. (4 If A is put into row echelon form then the diagonal entries of he result are nonzero. (5 If A is put into reduced row echelon form then the result is the identity matrix.

11 List as many properties as you can of a nonsingular matrix. Answer: Suppose that A is nonsingular. Then: ( A is invertible. (2 The only solution of the homogeneous system Ay = is the zero vector. (3 The equation Ax = b has a unique solution for any right hand side b. (4 If A is put into row echelon form then the diagonal entries of he result are nonzero. (5 If A is put into reduced row echelon form then the result is the identity matrix Find the nullspace of the matrix ( Answer: The nullspace consists of solutions of ( ( ( 4 4 x =. 2 2 y Set up the augmented matrix and reduce to row echelon form. ( ( Hence, y is free and x + y = x = y. Therefore, all solutions have the form ( ( ( x y x = = = y, y y where y is free Find the nullspace of the matrix ( Answer: We use row operations to reduce A to row echelon form ( 3. Hence z is a free variable. We backsolve to find that y = and x = y z = z. Hence the nullspace consists of all vectors of the form ( ( ( x z v = y = = z. z z

12 Find the nullspace of the matrix Answer: We use row operations to reduce A to row echelon form We set the free variables y 3 = s and y 4 = t. Then we backsolve to find that y 2 = y 4 = t, and then that y = [2y 2 + 4y 3 + 4y 4 ]/2 = 2s + t. Hence the nullspace consists of all vectors of the form y y 2 y = = y 3 y 4 2s + t t s t 2 = s + t Either show that the following vectors are linearly independent or find a nontrivial linear combination that is equal to. ( ( v = and v 2 2 = 3 Answer: We must examine the nullspace of the matrix V = [v, v 2 ]. Using row operations we get ( ( V = Since the diagonal entries are nonzero, V is nonsingular, and its nullspace is trivial (i.e., it contains only the zero vector. Hence v and v 2 are linearly independent Either show that the following vectors are linearly independent or find a nontrivial linear combination that is equal to. ( 8 ( 2 ( 8 v = 9 6, v 2 = 7 and v 3 = 8 4 Answer: We must examine the nullspace of the matrix V = [v, v 2, v 3 ]. Using row operations we transform V to row echelon form ( Thus we see that the third component is free or y 3 = t. We backsolve for y 2 = 4y 3 = 4t, and y = [8y 3 2y 2 ]/8 = 2t. Hence the nullspace of V consists of all vectors of the form t(2, 4, T. Taking t = we have the vector (2, 4, T. Hence we have 2v 4v 2 + v 3 =,.

13 so v, v 2, and v 3 are linearly dependent Find a basis for the span of the vectors v and v 2 in Exercise What is the dimension of the span? Answer: Since the vectors v and v 2 are linearly independent, they form a basis for their span. Since there are two vectors in the basis, the dimension is Find a basis for the span of the vectors v, v 2, and v 3 in Exercise What is the dimension of the span? Answer: Since v, v 2, and v 3 are linearly dependent, they do not form a basis. From Exercise we know that 2v 4v 2 + v 3 =, or v 3 = 4v 2 2v. Hence any vector in the spaesn of v, v 2, and v 3 can be written as a v + a 2 v 2 + a 3 v 3 = a v + a 2 v 2 + a 3 (4v 2 2v = (a 2a 3 v + (a 2 + 4a 3 v 2. Thus every vector in the span of v, v 2, and v 3 is also in the span of v and v 2. Furthermore, since the vectors v and v 2 are not multiples of each other, they are linearly independent. Hence they form a basis of the span of v, v 2, and v 3. The dimension of the span is Find a basis for the nullspace of the matrix in Exercise Answer: In Exercise we found that the nullspace consists of all vectors of the form 2 y = s + t. Let v = (2,,, T and v 2 = (,,, T. We see that v and v 2 span the nullspace. In addition they are not multiples of each other, so they form a basis Describe the solution space of the system Ax = b, where A is the matrix in Exercise 7.5.3, and b = (4, 2 T. Answer: By observation we find that v p = (, T is a particular solution to the system. In Exercise we found that the nullspace is generated by v h = (, T. Hence the solution space to the system Ax = b consists of all vectors of the form x = v p + tv h, where t R Describe the solution space of the system Ax = b, where A is the matrix in Exercise and b = (, 6,, 6 T. Answer: By observation we find that v p = (3,,, T is a particular solution. In Exercise we discovered that the nullspace of A has as a basis the vectors v = (2,,, T and v 2 = (,,, T. Hence every solution to the system Ax = b is of the form x = v p + sv + tv 2, where s, t R.

14 M9.2c. Answer: Using MATLAB we do the following: >> A=[-9, -28, 8, 38; 8, 6, -27, -6; 2, 4, 2, -4; -8, -6, 2, 6]; >> b = [3; 5; -2; -4]; >> [A, b] >> rref(m ans= -2 Since the right hand column contains a pivot, we know that the system is inconsistent. There are no solutions. M9.2f. Answer: Using MATLAB we do the following: >> A = [-23, 26, -42, -32, -9; -2,,, -3, -4; -7, 9, -28, -22, -63; -4, 4, -24, -6, -52; 8, -2, 32, 23, 69]; >> b = [-6; -2; -3; -2; 3];

15 >> [A, b] >> rref(m ans= Now we backsolve and discover that the solution space is the single point x = (,,,, T. This problem can also be done with the single command >> A\b ans= M9.3f. Answer: Using MATLAB we do the following: >> A = [6, -4, 2, -2, -8; 6, -4, 2, -2, -8; 29, -4,, -54, -36; 3, -6, 5, -24, -6; -, 4, -4, 8, 2]

16 A = >> null(a, r ans= M9.4g. Thus the three vectors /2 3/2 /4 3/4 /2 v =, v 2 = and v 3 = are a basis of the nullspace of A. The dimension is 3. Answer: >> v = [; ; ; ]; >> v2 = [; ; ; ]; >> v3 = [5; -6; ; -6]; >> V = [v, v2, v3] V = >> null(v, r ans= Empty matrix: 3-by- This means that the nullspace is trivial, so the vectors are linearly independent.

2. Every linear system with the same number of equations as unknowns has a unique solution.

2. Every linear system with the same number of equations as unknowns has a unique solution. 1. For matrices A, B, C, A + B = A + C if and only if A = B. 2. Every linear system with the same number of equations as unknowns has a unique solution. 3. Every linear system with the same number of equations

More information

MATH 2331 Linear Algebra. Section 2.1 Matrix Operations. Definition: A : m n, B : n p. Example: Compute AB, if possible.

MATH 2331 Linear Algebra. Section 2.1 Matrix Operations. Definition: A : m n, B : n p. Example: Compute AB, if possible. MATH 2331 Linear Algebra Section 2.1 Matrix Operations Definition: A : m n, B : n p ( 1 2 p ) ( 1 2 p ) AB = A b b b = Ab Ab Ab Example: Compute AB, if possible. 1 Row-column rule: i-j-th entry of AB:

More information

Math 2174: Practice Midterm 1

Math 2174: Practice Midterm 1 Math 74: Practice Midterm Show your work and explain your reasoning as appropriate. No calculators. One page of handwritten notes is allowed for the exam, as well as one blank page of scratch paper.. Consider

More information

MATH 2360 REVIEW PROBLEMS

MATH 2360 REVIEW PROBLEMS MATH 2360 REVIEW PROBLEMS Problem 1: In (a) (d) below, either compute the matrix product or indicate why it does not exist: ( )( ) 1 2 2 1 (a) 0 1 1 2 ( ) 0 1 2 (b) 0 3 1 4 3 4 5 2 5 (c) 0 3 ) 1 4 ( 1

More information

Midterm 1 Review. Written by Victoria Kala SH 6432u Office Hours: R 12:30 1:30 pm Last updated 10/10/2015

Midterm 1 Review. Written by Victoria Kala SH 6432u Office Hours: R 12:30 1:30 pm Last updated 10/10/2015 Midterm 1 Review Written by Victoria Kala vtkala@math.ucsb.edu SH 6432u Office Hours: R 12:30 1:30 pm Last updated 10/10/2015 Summary This Midterm Review contains notes on sections 1.1 1.5 and 1.7 in your

More information

Math 314H EXAM I. 1. (28 points) The row reduced echelon form of the augmented matrix for the system. is the matrix

Math 314H EXAM I. 1. (28 points) The row reduced echelon form of the augmented matrix for the system. is the matrix Math 34H EXAM I Do all of the problems below. Point values for each of the problems are adjacent to the problem number. Calculators may be used to check your answer but not to arrive at your answer. That

More information

Chapter 1. Vectors, Matrices, and Linear Spaces

Chapter 1. Vectors, Matrices, and Linear Spaces 1.6 Homogeneous Systems, Subspaces and Bases 1 Chapter 1. Vectors, Matrices, and Linear Spaces 1.6. Homogeneous Systems, Subspaces and Bases Note. In this section we explore the structure of the solution

More information

Linear Independence x

Linear Independence x Linear Independence A consistent system of linear equations with matrix equation Ax = b, where A is an m n matrix, has a solution set whose graph in R n is a linear object, that is, has one of only n +

More information

x = t 1 x 1 + t 2 x t k x k

x = t 1 x 1 + t 2 x t k x k Def.: Given vectors x,...,x k in R n, the set of all their linear combinations is called their span, and is denoted by span(x,...,x k ) Thm.: span(x,...,x k ) is a subspace of R n Def.: If V is a subspace

More information

Row Space, Column Space, and Nullspace

Row Space, Column Space, and Nullspace Row Space, Column Space, and Nullspace MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Introduction Every matrix has associated with it three vector spaces: row space

More information

Matrix equation Ax = b

Matrix equation Ax = b Fall 2017 Matrix equation Ax = b Authors: Alexander Knop Institute: UC San Diego Previously On Math 18 DEFINITION If v 1,..., v l R n, then a set of all linear combinations of them is called Span {v 1,...,

More information

MATH 2331 Linear Algebra. Section 1.1 Systems of Linear Equations. Finding the solution to a set of two equations in two variables: Example 1: Solve:

MATH 2331 Linear Algebra. Section 1.1 Systems of Linear Equations. Finding the solution to a set of two equations in two variables: Example 1: Solve: MATH 2331 Linear Algebra Section 1.1 Systems of Linear Equations Finding the solution to a set of two equations in two variables: Example 1: Solve: x x = 3 1 2 2x + 4x = 12 1 2 Geometric meaning: Do these

More information

MA 242 LINEAR ALGEBRA C1, Solutions to First Midterm Exam

MA 242 LINEAR ALGEBRA C1, Solutions to First Midterm Exam MA 242 LINEAR ALGEBRA C Solutions to First Midterm Exam Prof Nikola Popovic October 2 9:am - :am Problem ( points) Determine h and k such that the solution set of x + = k 4x + h = 8 (a) is empty (b) contains

More information

MATH10212 Linear Algebra B Homework Week 4

MATH10212 Linear Algebra B Homework Week 4 MATH22 Linear Algebra B Homework Week 4 Students are strongly advised to acquire a copy of the Textbook: D. C. Lay Linear Algebra and its Applications. Pearson, 26. ISBN -52-2873-4. Normally, homework

More information

Linear Algebra Exam 1 Spring 2007

Linear Algebra Exam 1 Spring 2007 Linear Algebra Exam 1 Spring 2007 March 15, 2007 Name: SOLUTION KEY (Total 55 points, plus 5 more for Pledged Assignment.) Honor Code Statement: Directions: Complete all problems. Justify all answers/solutions.

More information

1. Determine by inspection which of the following sets of vectors is linearly independent. 3 3.

1. Determine by inspection which of the following sets of vectors is linearly independent. 3 3. 1. Determine by inspection which of the following sets of vectors is linearly independent. (a) (d) 1, 3 4, 1 { [ [,, 1 1] 3]} (b) 1, 4 5, (c) 3 6 (e) 1, 3, 4 4 3 1 4 Solution. The answer is (a): v 1 is

More information

Math 369 Exam #2 Practice Problem Solutions

Math 369 Exam #2 Practice Problem Solutions Math 369 Exam #2 Practice Problem Solutions 2 5. Is { 2, 3, 8 } a basis for R 3? Answer: No, it is not. To show that it is not a basis, it suffices to show that this is not a linearly independent set.

More information

The matrix will only be consistent if the last entry of row three is 0, meaning 2b 3 + b 2 b 1 = 0.

The matrix will only be consistent if the last entry of row three is 0, meaning 2b 3 + b 2 b 1 = 0. ) Find all solutions of the linear system. Express the answer in vector form. x + 2x + x + x 5 = 2 2x 2 + 2x + 2x + x 5 = 8 x + 2x + x + 9x 5 = 2 2 Solution: Reduce the augmented matrix [ 2 2 2 8 ] to

More information

Chapter 3. Directions: For questions 1-11 mark each statement True or False. Justify each answer.

Chapter 3. Directions: For questions 1-11 mark each statement True or False. Justify each answer. Chapter 3 Directions: For questions 1-11 mark each statement True or False. Justify each answer. 1. (True False) Asking whether the linear system corresponding to an augmented matrix [ a 1 a 2 a 3 b ]

More information

Review for Chapter 1. Selected Topics

Review for Chapter 1. Selected Topics Review for Chapter 1 Selected Topics Linear Equations We have four equivalent ways of writing linear systems: 1 As a system of equations: 2x 1 + 3x 2 = 7 x 1 x 2 = 5 2 As an augmented matrix: ( 2 3 ) 7

More information

1. TRUE or FALSE. 2. Find the complete solution set to the system:

1. TRUE or FALSE. 2. Find the complete solution set to the system: TRUE or FALSE (a A homogenous system with more variables than equations has a nonzero solution True (The number of pivots is going to be less than the number of columns and therefore there is a free variable

More information

Determine whether the following system has a trivial solution or non-trivial solution:

Determine whether the following system has a trivial solution or non-trivial solution: Practice Questions Lecture # 7 and 8 Question # Determine whether the following system has a trivial solution or non-trivial solution: x x + x x x x x The coefficient matrix is / R, R R R+ R The corresponding

More information

MATH 2050 Assignment 6 Fall 2018 Due: Thursday, November 1. x + y + 2z = 2 x + y + z = c 4x + 2z = 2

MATH 2050 Assignment 6 Fall 2018 Due: Thursday, November 1. x + y + 2z = 2 x + y + z = c 4x + 2z = 2 MATH 5 Assignment 6 Fall 8 Due: Thursday, November [5]. For what value of c does have a solution? Is it unique? x + y + z = x + y + z = c 4x + z = Writing the system as an augmented matrix, we have c R

More information

MATH 1120 (LINEAR ALGEBRA 1), FINAL EXAM FALL 2011 SOLUTIONS TO PRACTICE VERSION

MATH 1120 (LINEAR ALGEBRA 1), FINAL EXAM FALL 2011 SOLUTIONS TO PRACTICE VERSION MATH (LINEAR ALGEBRA ) FINAL EXAM FALL SOLUTIONS TO PRACTICE VERSION Problem (a) For each matrix below (i) find a basis for its column space (ii) find a basis for its row space (iii) determine whether

More information

Find the general solution of the system y = Ay, where

Find the general solution of the system y = Ay, where Math Homework # March, 9..3. Find the general solution of the system y = Ay, where 5 Answer: The matrix A has characteristic polynomial p(λ = λ + 7λ + = λ + 3(λ +. Hence the eigenvalues are λ = 3and λ

More information

MATH10212 Linear Algebra B Homework 6. Be prepared to answer the following oral questions if asked in the supervision class:

MATH10212 Linear Algebra B Homework 6. Be prepared to answer the following oral questions if asked in the supervision class: MATH0 Linear Algebra B Homework 6 Students are strongly advised to acquire a copy of the Textbook: D C Lay, Linear Algebra its Applications Pearson, 006 (or other editions) Normally, homework assignments

More information

Check that your exam contains 20 multiple-choice questions, numbered sequentially.

Check that your exam contains 20 multiple-choice questions, numbered sequentially. MATH 22 MAKEUP EXAMINATION Fall 26 VERSION A NAME STUDENT NUMBER INSTRUCTOR SECTION NUMBER On your scantron, write and bubble your PSU ID, Section Number, and Test Version. Failure to correctly code these

More information

YORK UNIVERSITY. Faculty of Science Department of Mathematics and Statistics MATH M Test #1. July 11, 2013 Solutions

YORK UNIVERSITY. Faculty of Science Department of Mathematics and Statistics MATH M Test #1. July 11, 2013 Solutions YORK UNIVERSITY Faculty of Science Department of Mathematics and Statistics MATH 222 3. M Test # July, 23 Solutions. For each statement indicate whether it is always TRUE or sometimes FALSE. Note: For

More information

Math 2940: Prelim 1 Practice Solutions

Math 2940: Prelim 1 Practice Solutions Math 294: Prelim Practice Solutions x. Find all solutions x = x 2 x 3 to the following system of equations: x 4 2x + 4x 2 + 2x 3 + 2x 4 = 6 x + 2x 2 + x 3 + x 4 = 3 3x 6x 2 + x 3 + 5x 4 = 5 Write your

More information

Math Final December 2006 C. Robinson

Math Final December 2006 C. Robinson Math 285-1 Final December 2006 C. Robinson 2 5 8 5 1 2 0-1 0 1. (21 Points) The matrix A = 1 2 2 3 1 8 3 2 6 has the reduced echelon form U = 0 0 1 2 0 0 0 0 0 1. 2 6 1 0 0 0 0 0 a. Find a basis for the

More information

Glossary of Linear Algebra Terms. Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

Glossary of Linear Algebra Terms. Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB Glossary of Linear Algebra Terms Basis (for a subspace) A linearly independent set of vectors that spans the space Basic Variable A variable in a linear system that corresponds to a pivot column in the

More information

Lecture 6: Spanning Set & Linear Independency

Lecture 6: Spanning Set & Linear Independency Lecture 6: Elif Tan Ankara University Elif Tan (Ankara University) Lecture 6 / 0 Definition (Linear Combination) Let v, v 2,..., v k be vectors in (V,, ) a vector space. A vector v V is called a linear

More information

Solution Set 3, Fall '12

Solution Set 3, Fall '12 Solution Set 3, 86 Fall '2 Do Problem 5 from 32 [ 3 5 Solution (a) A = Only one elimination step is needed to produce the 2 6 echelon form The pivot is the in row, column, and the entry to eliminate is

More information

3.4 Elementary Matrices and Matrix Inverse

3.4 Elementary Matrices and Matrix Inverse Math 220: Summer 2015 3.4 Elementary Matrices and Matrix Inverse A n n elementary matrix is a matrix which is obtained from the n n identity matrix I n n by a single elementary row operation. Elementary

More information

MATH 3321 Sample Questions for Exam 3. 3y y, C = Perform the indicated operations, if possible: (a) AC (b) AB (c) B + AC (d) CBA

MATH 3321 Sample Questions for Exam 3. 3y y, C = Perform the indicated operations, if possible: (a) AC (b) AB (c) B + AC (d) CBA MATH 33 Sample Questions for Exam 3. Find x and y so that x 4 3 5x 3y + y = 5 5. x = 3/7, y = 49/7. Let A = 3 4, B = 3 5, C = 3 Perform the indicated operations, if possible: a AC b AB c B + AC d CBA AB

More information

Chapter 1: Systems of Linear Equations

Chapter 1: Systems of Linear Equations Chapter : Systems of Linear Equations February, 9 Systems of linear equations Linear systems Lecture A linear equation in variables x, x,, x n is an equation of the form a x + a x + + a n x n = b, where

More information

1. Let m 1 and n 1 be two natural numbers such that m > n. Which of the following is/are true?

1. Let m 1 and n 1 be two natural numbers such that m > n. Which of the following is/are true? . Let m and n be two natural numbers such that m > n. Which of the following is/are true? (i) A linear system of m equations in n variables is always consistent. (ii) A linear system of n equations in

More information

Elementary Matrices. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Elementary Matrices. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics Elementary Matrices MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Outline Today s discussion will focus on: elementary matrices and their properties, using elementary

More information

SECTION 3.3. PROBLEM 22. The null space of a matrix A is: N(A) = {X : AX = 0}. Here are the calculations of AX for X = a,b,c,d, and e. =

SECTION 3.3. PROBLEM 22. The null space of a matrix A is: N(A) = {X : AX = 0}. Here are the calculations of AX for X = a,b,c,d, and e. = SECTION 3.3. PROBLEM. The null space of a matrix A is: N(A) {X : AX }. Here are the calculations of AX for X a,b,c,d, and e. Aa [ ][ ] 3 3 [ ][ ] Ac 3 3 [ ] 3 3 [ ] 4+4 6+6 Ae [ ], Ab [ ][ ] 3 3 3 [ ]

More information

Linear Equations in Linear Algebra

Linear Equations in Linear Algebra Linear Equations in Linear Algebra.7 LINEAR INDEPENDENCE LINEAR INDEPENDENCE Definition: An indexed set of vectors {v,, v p } in n is said to be linearly independent if the vector equation x x x 2 2 p

More information

MATH 152 Exam 1-Solutions 135 pts. Write your answers on separate paper. You do not need to copy the questions. Show your work!!!

MATH 152 Exam 1-Solutions 135 pts. Write your answers on separate paper. You do not need to copy the questions. Show your work!!! MATH Exam -Solutions pts Write your answers on separate paper. You do not need to copy the questions. Show your work!!!. ( pts) Find the reduced row echelon form of the matrix Solution : 4 4 6 4 4 R R

More information

Lecture 6 & 7. Shuanglin Shao. September 16th and 18th, 2013

Lecture 6 & 7. Shuanglin Shao. September 16th and 18th, 2013 Lecture 6 & 7 Shuanglin Shao September 16th and 18th, 2013 1 Elementary matrices 2 Equivalence Theorem 3 A method of inverting matrices Def An n n matrice is called an elementary matrix if it can be obtained

More information

Math 3C Lecture 20. John Douglas Moore

Math 3C Lecture 20. John Douglas Moore Math 3C Lecture 20 John Douglas Moore May 18, 2009 TENTATIVE FORMULA I Midterm I: 20% Midterm II: 20% Homework: 10% Quizzes: 10% Final: 40% TENTATIVE FORMULA II Higher of two midterms: 30% Homework: 10%

More information

BASIC NOTIONS. x + y = 1 3, 3x 5y + z = A + 3B,C + 2D, DC are not defined. A + C =

BASIC NOTIONS. x + y = 1 3, 3x 5y + z = A + 3B,C + 2D, DC are not defined. A + C = CHAPTER I BASIC NOTIONS (a) 8666 and 8833 (b) a =6,a =4 will work in the first case, but there are no possible such weightings to produce the second case, since Student and Student 3 have to end up with

More information

Chapter 2 Notes, Linear Algebra 5e Lay

Chapter 2 Notes, Linear Algebra 5e Lay Contents.1 Operations with Matrices..................................1.1 Addition and Subtraction.............................1. Multiplication by a scalar............................ 3.1.3 Multiplication

More information

Review Notes for Linear Algebra True or False Last Updated: February 22, 2010

Review Notes for Linear Algebra True or False Last Updated: February 22, 2010 Review Notes for Linear Algebra True or False Last Updated: February 22, 2010 Chapter 4 [ Vector Spaces 4.1 If {v 1,v 2,,v n } and {w 1,w 2,,w n } are linearly independent, then {v 1 +w 1,v 2 +w 2,,v n

More information

MATH10212 Linear Algebra B Homework 7

MATH10212 Linear Algebra B Homework 7 MATH22 Linear Algebra B Homework 7 Students are strongly advised to acquire a copy of the Textbook: D C Lay, Linear Algebra and its Applications Pearson, 26 (or other editions) Normally, homework assignments

More information

Numerical Linear Algebra Homework Assignment - Week 2

Numerical Linear Algebra Homework Assignment - Week 2 Numerical Linear Algebra Homework Assignment - Week 2 Đoàn Trần Nguyên Tùng Student ID: 1411352 8th October 2016 Exercise 2.1: Show that if a matrix A is both triangular and unitary, then it is diagonal.

More information

1111: Linear Algebra I

1111: Linear Algebra I 1111: Linear Algebra I Dr. Vladimir Dotsenko (Vlad) Lecture 13 Dr. Vladimir Dotsenko (Vlad) 1111: Linear Algebra I Lecture 13 1 / 8 The coordinate vector space R n We already used vectors in n dimensions

More information

MATH10212 Linear Algebra B Homework Week 3. Be prepared to answer the following oral questions if asked in the supervision class

MATH10212 Linear Algebra B Homework Week 3. Be prepared to answer the following oral questions if asked in the supervision class MATH10212 Linear Algebra B Homework Week Students are strongly advised to acquire a copy of the Textbook: D. C. Lay Linear Algebra its Applications. Pearson, 2006. ISBN 0-521-2871-4. Normally, homework

More information

Rank and Nullity. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Rank and Nullity. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics Rank and Nullity MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Objectives We have defined and studied the important vector spaces associated with matrices (row space,

More information

Math 102, Winter 2009, Homework 7

Math 102, Winter 2009, Homework 7 Math 2, Winter 29, Homework 7 () Find the standard matrix of the linear transformation T : R 3 R 3 obtained by reflection through the plane x + z = followed by a rotation about the positive x-axes by 6

More information

Introduction to Determinants

Introduction to Determinants Introduction to Determinants For any square matrix of order 2, we have found a necessary and sufficient condition for invertibility. Indeed, consider the matrix The matrix A is invertible if and only if.

More information

Lecture 12: Solving Systems of Linear Equations by Gaussian Elimination

Lecture 12: Solving Systems of Linear Equations by Gaussian Elimination Lecture 12: Solving Systems of Linear Equations by Gaussian Elimination Winfried Just, Ohio University September 22, 2017 Review: The coefficient matrix Consider a system of m linear equations in n variables.

More information

Linear Algebra Math 221

Linear Algebra Math 221 Linear Algebra Math 221 Open Book Exam 1 Open Notes 3 Sept, 24 Calculators Permitted Show all work (except #4) 1 2 3 4 2 1. (25 pts) Given A 1 2 1, b 2 and c 4. 1 a) (7 pts) Bring matrix A to echelon form.

More information

Math 4A Notes. Written by Victoria Kala Last updated June 11, 2017

Math 4A Notes. Written by Victoria Kala Last updated June 11, 2017 Math 4A Notes Written by Victoria Kala vtkala@math.ucsb.edu Last updated June 11, 2017 Systems of Linear Equations A linear equation is an equation that can be written in the form a 1 x 1 + a 2 x 2 +...

More information

Matrices and RRE Form

Matrices and RRE Form Matrices and RRE Form Notation R is the real numbers, C is the complex numbers (we will only consider complex numbers towards the end of the course) is read as an element of For instance, x R means that

More information

Mid-term Exam #1 MATH 205, Fall 2014

Mid-term Exam #1 MATH 205, Fall 2014 Mid-term Exam # MATH, Fall Name: Instructions: Please answer as many of the following questions as possible. Show all of your work and give complete explanations when requested. Write your final answer

More information

Column 3 is fine, so it remains to add Row 2 multiplied by 2 to Row 1. We obtain

Column 3 is fine, so it remains to add Row 2 multiplied by 2 to Row 1. We obtain Section Exercise : We are given the following augumented matrix 3 7 6 3 We have to bring it to the diagonal form The entries below the diagonal are already zero, so we work from bottom to top Adding the

More information

Study Guide for Linear Algebra Exam 2

Study Guide for Linear Algebra Exam 2 Study Guide for Linear Algebra Exam 2 Term Vector Space Definition A Vector Space is a nonempty set V of objects, on which are defined two operations, called addition and multiplication by scalars (real

More information

Additional Homework Problems

Additional Homework Problems Math 216 2016-2017 Fall Additional Homework Problems 1 In parts (a) and (b) assume that the given system is consistent For each system determine all possibilities for the numbers r and n r where r is the

More information

(c)

(c) 1. Find the reduced echelon form of the matrix 1 1 5 1 8 5. 1 1 1 (a) 3 1 3 0 1 3 1 (b) 0 0 1 (c) 3 0 0 1 0 (d) 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 (e) 1 0 5 0 0 1 3 0 0 0 0 Solution. 1 1 1 1 1 1 1 1

More information

Math 60. Rumbos Spring Solutions to Assignment #17

Math 60. Rumbos Spring Solutions to Assignment #17 Math 60. Rumbos Spring 2009 1 Solutions to Assignment #17 a b 1. Prove that if ad bc 0 then the matrix A = is invertible and c d compute A 1. a b Solution: Let A = and assume that ad bc 0. c d First consider

More information

6.4 Basis and Dimension

6.4 Basis and Dimension 6.4 Basis and Dimension DEF ( p. 263) AsetS ={v 1, v 2, v k } of vectors in a vector space V is a basis for V if (1) S spans V and (2) S is linearly independent. MATH 316U (003) - 6.4 (Basis and Dimension)

More information

Chapter 1: Systems of linear equations and matrices. Section 1.1: Introduction to systems of linear equations

Chapter 1: Systems of linear equations and matrices. Section 1.1: Introduction to systems of linear equations Chapter 1: Systems of linear equations and matrices Section 1.1: Introduction to systems of linear equations Definition: A linear equation in n variables can be expressed in the form a 1 x 1 + a 2 x 2

More information

web: HOMEWORK 1

web:   HOMEWORK 1 MAT 207 LINEAR ALGEBRA I 2009207 Dokuz Eylül University, Faculty of Science, Department of Mathematics Instructor: Engin Mermut web: http://kisideuedutr/enginmermut/ HOMEWORK VECTORS IN THE n-dimensional

More information

Section 2.2: The Inverse of a Matrix

Section 2.2: The Inverse of a Matrix Section 22: The Inverse of a Matrix Recall that a linear equation ax b, where a and b are scalars and a 0, has the unique solution x a 1 b, where a 1 is the reciprocal of a From this result, it is natural

More information

Chapter 1. Vectors, Matrices, and Linear Spaces

Chapter 1. Vectors, Matrices, and Linear Spaces 1.4 Solving Systems of Linear Equations 1 Chapter 1. Vectors, Matrices, and Linear Spaces 1.4. Solving Systems of Linear Equations Note. We give an algorithm for solving a system of linear equations (called

More information

Solutions to Homework 5 - Math 3410

Solutions to Homework 5 - Math 3410 Solutions to Homework 5 - Math 34 (Page 57: # 489) Determine whether the following vectors in R 4 are linearly dependent or independent: (a) (, 2, 3, ), (3, 7,, 2), (, 3, 7, 4) Solution From x(, 2, 3,

More information

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 1 x 2. x n 8 (4) 3 4 2

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 1 x 2. x n 8 (4) 3 4 2 MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS SYSTEMS OF EQUATIONS AND MATRICES Representation of a linear system The general system of m equations in n unknowns can be written a x + a 2 x 2 + + a n x n b a

More information

System of Linear Equations

System of Linear Equations Math 20F Linear Algebra Lecture 2 1 System of Linear Equations Slide 1 Definition 1 Fix a set of numbers a ij, b i, where i = 1,, m and j = 1,, n A system of m linear equations in n variables x j, is given

More information

Section 1.2. Row Reduction and Echelon Forms

Section 1.2. Row Reduction and Echelon Forms Section 1.2 Row Reduction and Echelon Forms Row Echelon Form Let s come up with an algorithm for turning an arbitrary matrix into a solved matrix. What do we mean by solved? A matrix is in row echelon

More information

MATH 20F: LINEAR ALGEBRA LECTURE B00 (T. KEMP)

MATH 20F: LINEAR ALGEBRA LECTURE B00 (T. KEMP) MATH 20F: LINEAR ALGEBRA LECTURE B00 (T KEMP) Definition 01 If T (x) = Ax is a linear transformation from R n to R m then Nul (T ) = {x R n : T (x) = 0} = Nul (A) Ran (T ) = {Ax R m : x R n } = {b R m

More information

Homework Set #8 Solutions

Homework Set #8 Solutions Exercises.2 (p. 19) Homework Set #8 Solutions Assignment: Do #6, 8, 12, 14, 2, 24, 26, 29, 0, 2, 4, 5, 6, 9, 40, 42 6. Reducing the matrix to echelon form: 1 5 2 1 R2 R2 R1 1 5 0 18 12 2 1 R R 2R1 1 5

More information

MA 1B PRACTICAL - HOMEWORK SET 3 SOLUTIONS. Solution. (d) We have matrix form Ax = b and vector equation 4

MA 1B PRACTICAL - HOMEWORK SET 3 SOLUTIONS. Solution. (d) We have matrix form Ax = b and vector equation 4 MA B PRACTICAL - HOMEWORK SET SOLUTIONS (Reading) ( pts)[ch, Problem (d), (e)] Solution (d) We have matrix form Ax = b and vector equation 4 i= x iv i = b, where v i is the ith column of A, and 4 A = 8

More information

MATH 323 Linear Algebra Lecture 12: Basis of a vector space (continued). Rank and nullity of a matrix.

MATH 323 Linear Algebra Lecture 12: Basis of a vector space (continued). Rank and nullity of a matrix. MATH 323 Linear Algebra Lecture 12: Basis of a vector space (continued). Rank and nullity of a matrix. Basis Definition. Let V be a vector space. A linearly independent spanning set for V is called a basis.

More information

Chapters 5 & 6: Theory Review: Solutions Math 308 F Spring 2015

Chapters 5 & 6: Theory Review: Solutions Math 308 F Spring 2015 Chapters 5 & 6: Theory Review: Solutions Math 308 F Spring 205. If A is a 3 3 triangular matrix, explain why det(a) is equal to the product of entries on the diagonal. If A is a lower triangular or diagonal

More information

Linear Equations in Linear Algebra

Linear Equations in Linear Algebra 1 Linear Equations in Linear Algebra 1.4 THE MATRIX EQUATION A = b MATRIX EQUATION A = b m n Definition: If A is an matri, with columns a 1, n, a n, and if is in, then the product of A and, denoted by

More information

Problem Sheet 1 with Solutions GRA 6035 Mathematics

Problem Sheet 1 with Solutions GRA 6035 Mathematics Problem Sheet 1 with Solutions GRA 6035 Mathematics BI Norwegian Business School 2 Problems 1. From linear system to augmented matrix Write down the coefficient matrix and the augmented matrix of the following

More information

Topics. Vectors (column matrices): Vector addition and scalar multiplication The matrix of a linear function y Ax The elements of a matrix A : A ij

Topics. Vectors (column matrices): Vector addition and scalar multiplication The matrix of a linear function y Ax The elements of a matrix A : A ij Topics Vectors (column matrices): Vector addition and scalar multiplication The matrix of a linear function y Ax The elements of a matrix A : A ij or a ij lives in row i and column j Definition of a matrix

More information

Math "Matrix Approach to Solving Systems" Bibiana Lopez. November Crafton Hills College. (CHC) 6.3 November / 25

Math Matrix Approach to Solving Systems Bibiana Lopez. November Crafton Hills College. (CHC) 6.3 November / 25 Math 102 6.3 "Matrix Approach to Solving Systems" Bibiana Lopez Crafton Hills College November 2010 (CHC) 6.3 November 2010 1 / 25 Objectives: * Define a matrix and determine its order. * Write the augmented

More information

Row Reduction and Echelon Forms

Row Reduction and Echelon Forms Row Reduction and Echelon Forms 1 / 29 Key Concepts row echelon form, reduced row echelon form pivot position, pivot, pivot column basic variable, free variable general solution, parametric solution existence

More information

Review Let A, B, and C be matrices of the same size, and let r and s be scalars. Then

Review Let A, B, and C be matrices of the same size, and let r and s be scalars. Then 1 Sec 21 Matrix Operations Review Let A, B, and C be matrices of the same size, and let r and s be scalars Then (i) A + B = B + A (iv) r(a + B) = ra + rb (ii) (A + B) + C = A + (B + C) (v) (r + s)a = ra

More information

A matrix is a rectangular array of. objects arranged in rows and columns. The objects are called the entries. is called the size of the matrix, and

A matrix is a rectangular array of. objects arranged in rows and columns. The objects are called the entries. is called the size of the matrix, and Section 5.5. Matrices and Vectors A matrix is a rectangular array of objects arranged in rows and columns. The objects are called the entries. A matrix with m rows and n columns is called an m n matrix.

More information

Spring 2014 Math 272 Final Exam Review Sheet

Spring 2014 Math 272 Final Exam Review Sheet Spring 2014 Math 272 Final Exam Review Sheet You will not be allowed use of a calculator or any other device other than your pencil or pen and some scratch paper. Notes are also not allowed. In kindness

More information

EBG # 3 Using Gaussian Elimination (Echelon Form) Gaussian Elimination: 0s below the main diagonal

EBG # 3 Using Gaussian Elimination (Echelon Form) Gaussian Elimination: 0s below the main diagonal EBG # 3 Using Gaussian Elimination (Echelon Form) Gaussian Elimination: 0s below the main diagonal [ x y Augmented matrix: 1 1 17 4 2 48 (Replacement) Replace a row by the sum of itself and a multiple

More information

b for the linear system x 1 + x 2 + a 2 x 3 = a x 1 + x 3 = 3 x 1 + x 2 + 9x 3 = 3 ] 1 1 a 2 a

b for the linear system x 1 + x 2 + a 2 x 3 = a x 1 + x 3 = 3 x 1 + x 2 + 9x 3 = 3 ] 1 1 a 2 a Practice Exercises for Exam Exam will be on Monday, September 8, 7. The syllabus for Exam consists of Sections One.I, One.III, Two.I, and Two.II. You should know the main definitions, results and computational

More information

Chapter 3: Theory Review: Solutions Math 308 F Spring 2015

Chapter 3: Theory Review: Solutions Math 308 F Spring 2015 Chapter : Theory Review: Solutions Math 08 F Spring 05. What two properties must a function T : R m R n satisfy to be a linear transformation? (a) For all vectors u and v in R m, T (u + v) T (u) + T (v)

More information

1 Linear systems, existence, uniqueness

1 Linear systems, existence, uniqueness Jor-el Briones / Math 2F, 25 Summer Session, Practice Midterm Page of 9 Linear systems, existence, uniqueness For each part, construct an augmented matrix for a linear system with the given properties,

More information

Math 54 HW 4 solutions

Math 54 HW 4 solutions Math 54 HW 4 solutions 2.2. Section 2.2 (a) False: Recall that performing a series of elementary row operations A is equivalent to multiplying A by a series of elementary matrices. Suppose that E,...,

More information

A matrix is a rectangular array of. objects arranged in rows and columns. The objects are called the entries. is called the size of the matrix, and

A matrix is a rectangular array of. objects arranged in rows and columns. The objects are called the entries. is called the size of the matrix, and Section 5.5. Matrices and Vectors A matrix is a rectangular array of objects arranged in rows and columns. The objects are called the entries. A matrix with m rows and n columns is called an m n matrix.

More information

MATH 54 - WORKSHEET 1 MONDAY 6/22

MATH 54 - WORKSHEET 1 MONDAY 6/22 MATH 54 - WORKSHEET 1 MONDAY 6/22 Row Operations: (1 (Replacement Add a multiple of one row to another row. (2 (Interchange Swap two rows. (3 (Scaling Multiply an entire row by a nonzero constant. A matrix

More information

Linear equations in linear algebra

Linear equations in linear algebra Linear equations in linear algebra Samy Tindel Purdue University Differential equations and linear algebra - MA 262 Taken from Differential equations and linear algebra Pearson Collections Samy T. Linear

More information

Math 54. Selected Solutions for Week 5

Math 54. Selected Solutions for Week 5 Math 54. Selected Solutions for Week 5 Section 4. (Page 94) 8. Consider the following two systems of equations: 5x + x 3x 3 = 5x + x 3x 3 = 9x + x + 5x 3 = 4x + x 6x 3 = 9 9x + x + 5x 3 = 5 4x + x 6x 3

More information

Section 1.1 System of Linear Equations. Dr. Abdulla Eid. College of Science. MATHS 211: Linear Algebra

Section 1.1 System of Linear Equations. Dr. Abdulla Eid. College of Science. MATHS 211: Linear Algebra Section 1.1 System of Linear Equations College of Science MATHS 211: Linear Algebra (University of Bahrain) Linear System 1 / 33 Goals:. 1 Define system of linear equations and their solutions. 2 To represent

More information

MTH 464: Computational Linear Algebra

MTH 464: Computational Linear Algebra MTH 464: Computational Linear Algebra Lecture Outlines Exam 2 Material Prof. M. Beauregard Department of Mathematics & Statistics Stephen F. Austin State University February 6, 2018 Linear Algebra (MTH

More information

Chapter 5. Linear Algebra. A linear (algebraic) equation in. unknowns, x 1, x 2,..., x n, is. an equation of the form

Chapter 5. Linear Algebra. A linear (algebraic) equation in. unknowns, x 1, x 2,..., x n, is. an equation of the form Chapter 5. Linear Algebra A linear (algebraic) equation in n unknowns, x 1, x 2,..., x n, is an equation of the form a 1 x 1 + a 2 x 2 + + a n x n = b where a 1, a 2,..., a n and b are real numbers. 1

More information

MATH 304 Linear Algebra Lecture 10: Linear independence. Wronskian.

MATH 304 Linear Algebra Lecture 10: Linear independence. Wronskian. MATH 304 Linear Algebra Lecture 10: Linear independence. Wronskian. Spanning set Let S be a subset of a vector space V. Definition. The span of the set S is the smallest subspace W V that contains S. If

More information

Systems of Linear Equations. By: Tri Atmojo Kusmayadi and Mardiyana Mathematics Education Sebelas Maret University

Systems of Linear Equations. By: Tri Atmojo Kusmayadi and Mardiyana Mathematics Education Sebelas Maret University Systems of Linear Equations By: Tri Atmojo Kusmayadi and Mardiyana Mathematics Education Sebelas Maret University Standard of Competency: Understanding the properties of systems of linear equations, matrices,

More information

Math 314H Solutions to Homework # 3

Math 314H Solutions to Homework # 3 Math 34H Solutions to Homework # 3 Complete the exercises from the second maple assignment which can be downloaded from my linear algebra course web page Attach printouts of your work on this problem to

More information